Real estate appraisal techniques are far from an exact science. Typically, the appraiser compares recent sales of the properties comparable to a subject property in order to determine the property's market value. Next, he adjusts the sales prices of comparable properties to reflect the physical characteristic differences from the subject property. Generally, this process may take several days to complete and it may also suffer from insufficient comparative results due to the time and other technical constraints. Furthermore, the preferred criterions by which comparative properties were selected are not always obvious or immediately available and therefore results are less verifiable.
Many automated valuation models (AVM) have been introduced to avoid some of the shortcomings of the traditional models.
“An AVM is a computer software program that analyses data using an automated process. For example, AVMs may use regression, adaptive estimation, neural network, expert reasoning, and artificial intelligence programs.
The output of an A VM is not, by itself, an appraisal. An AVM 's output may become basis for appraisal, appraisal review, or appraisal consulting opinion and conclusions if the appraiser believes the output to be credible and reliable for use in a specific assignment”. (USPAP 2003 Edition p.180)
U.S. Pat. No. 5,857,174 discloses a real estate appraisal method in which the buyer of a property assigns points to a subject property and each comparable property based upon an Ideal Point System (IPS). The points assigned (or IPS values) upon the desirability factors for each of five categories of criteria. The total possible IPS value for any property is 100, corresponding to a 100 percent desirability. Once the IPS values are determined, the property may be subsequently used as a comparable property. The appraiser needs only to select a subject property and to obtain the IPS values for the subject property. The sale price of each comparable property is then adjusted, based on the relative difference between the IPS values for the comparable properties and the IPS values of the subject property, by dividing the total IPS value for each comparable property by the IPS value for the subject property to obtain a composite adjustment ratio. The adjustment ratio for each comparable property is then multiplied by the sales price to obtain an adjusted sales price. Any greatly divergent adjusted sales prices are discarded, and the average adjusted sales price is determined. The average adjusted sales price is used as the appraised value for the subject property.
U.S. Pat. No. 5,414,621 discloses a system and method for determining comparative values of comparable properties based on assessment of percentages and sales data of the comparable properties to ultimately determine a value for a subject property. In a first embodiment, the “assessment percentage” is the “base property tax” for the subject property and comparable property. A price/tax factor is computed for each comparable property by dividing the sale (or sold) price of the comparable property by its base tax. The price/tax factor for each comparable property is then multiplied by the base tax of the subject property to generate a net comparative value for each comparable property. To take into account appreciation for recently sold comparable properties, an average appreciation is obtained for the area in which the subject and comparable properties are located. The average appreciation is pro rated to determine the comparative value for each comparable property. On the basis of the comparative values and other pertinent information, the value of the subject property may be set by a real estate agent, bank, appraiser, etc.
U.S. Pat. No. 6,058,369 discloses that by gathering information regarding the total number of sales, total number of pending listings, total number of active listings, and total number of expired listings in a time period, a market index may be derived. This market index can then be charted over a plurality of periods, giving an indication of any temporal trends. The market index can further be used to guide and determine the action of a service provider such as a lender or title insurance company in a proposed real estate transaction.
U.S. Pat. No. 6,178,406 B1 discloses a method for estimating the price of real estate property such as a single-family residence. A set of real estate properties comparable to the subject property is retrieved. The comparable properties and the subject property are characterized by a plurality of common attributes each having a respective value. Each attribute value from the comparable properties is evaluated to the same attribute value of the subject property on a fuzzy preference scale indicating desirable and tolerable deviations from an ideal match with the subject property. A measurement of similarity between each comparable property and the subject property is then determined. Next, the prices of the comparable properties are adjusted to the value of the subject property and the best properties are extracted for further consideration. The extracted comparable properties are then aggregated into an estimate price of the subject property.
U.S. Pat. No. 6,115,694 discloses a computer-implemented method for validating specified prices on real estate property. A set of real estate properties comparable to the subject property is retrieved. A measurement of similarity between each comparable property and the subject property is then determined. A plurality of adjustment rules is then applied to adjust the price of the comparable properties. The adjusted comparable properties are then extracted, sorted, and ranked, according to the specified sale price. The extracted comparable properties are then aggregated into an estimate price of the subject property. After aggregation, the estimate price of the subject property is compared to the specified price and a measurement of confidence validating the reliability of the specified price is then generated.
U.S. APP. A1 20020002494 discloses a system for facilitating appraisals. A lender and/or customer may request an appraisal from a hub. The hub checks the schedules of local appraisers, selects an appraiser and schedules the appraisal. Once the appraisal has been completed, the appraiser uploads the appraisal information and the hub transfers the information to the requestor or other customer. The hub may also store the appraisal and information about the uploaded appraisal for analysis regarding the appraised property or the appraiser's work product.
U.S. APP. A1 20010039506 discloses a real estate appraisal method wherein a database of enhanced records of properties in the same territory as the subject property is used to derive market-driven value adjustment rates for property attributes and time differentials. The adjustment rates are applied to the properties in the database, the most similar comparable properties are selected on the basis of similarity in property attributes and the market value is then estimated from the selected most similar comparable properties. The resulting valuation is supportable by market conditions and can be printed on specified forms.
U.S. APP. A1 20020147695 discloses a system for automating the process of valuing a property that produces an estimated value of a subject property, and a quality assessment of the estimated value. The process is a generative artificial intelligence method that trains a fuzzy-neural network using a subset of cases from a case-base, and produces a run-time system to provide an estimate of the subject property's value. In one embodiment, the system is a network-based implementation of a fuzzy inference based on a system that implements a fuzzy system as a five-layer neural network so that the structure of the network can be interpreted in terms of high-level rules. The neural network is trained automatically from data. IF/THEN rules are used to map inputs to outputs by a fuzzy logic inference system. Different models for the same problem can be obtained by changing the inputs to the neuro-fuzzy network, or by varying its architecture.
With the advancement of computer software and statistical models and methods such as Monte Carlo, simulation in income estimates became viable solution to otherwise lengthy analytical processes. Using this simulation in Discount Cash Flow (DCF) modeling, it became more feasible to quantitatively estimate the impact of uncertainty on the market value estimates and improve long-term investment decisions. Monte Carlo simulation also does not require rigorous certainty or normality assumptions about the input values.
Instead, each input in the model is represented by a probability density function, or a range of values that are possible, and not just a single, most likely value.
A simulation model allows users to run thousands of iterations quickly (each representing a separate “what if” analysis) and summarizes the entire range of possible outcomes efficiently providing practitioners with valuable insights about the relationship between outcomes and uncertain inputs. (The Appraisal Journal, January 2000, pp.44).
While the Monte Carlo simulation eliminates the problem of single-point values, this approach is used only in specific applications such as DCF modeling it is not generally used in overall appraisal process.
The appraiser services are now available in forms of commercial software, which was introduced to facilitate appraiser information processes.
A La Mode, Inc., providing an appraisal-related information and services including appraiser listings, technology/EDI updates, and software information;    ACI Development, providing a software solutions, including electronic forms, digital imaging, and communications software, for the real estate appraisal, home inspection, and insurance industries;    Appraiser's ToolBox, providing Windows (from the Microsoft Corporation) and Mac (from the Apple Computer, Inc.) form processing software with integrated tools;    CSA, Inc., providing Canadian appraisal forms (including the CERC) and CRAL software;    Day One, Inc., providing an office management systems and appraisal forms software;    Eminent Domain Software, providing a real estate software for appraisers, inspectors and tax assessors;    MicroSolve, providing software for local governments to assess property values and maintain property databases;    PSAR Systems, providing a residential appraisal software; and    United Systems Software Company, providing an appraisal software, electronic forms solutions, EDI, and artificial intelligence.
Many of these known AVM systems focus on providing an estimate of value that has been derived from a number of transactions. Often the analysis is made based on the property records (limited to parcel level inventories) sometimes of questionable quality. Generally, most of these models attempt to facilitate gathering of comparable data according to one appraisal approach, typically the market approach.
Other References Cited
Uniform Standards of Professional Appraisal Practice (USPAP) 2003 Edition
The Appraisal of Real Estate, Appraisal Institute
Valuation Under the Law of Eminent Domain, Lewis Orgel, 1953
Real Estate Valuation in Litigation, J. D. Eaton, Appraisal Institute, 1995
More, Jorge J. and Stephen J. Wright, Optimization Software Guide, Philadelphia: SIAM, 1993
The appraised values produced by different independent appraisers for the same property can vary by as much as 50%. The discrepancy in estimates can be attributed to several different factors but typically is caused by different sets of most “relevant units of comparisons” as developed in each estimating approach by various appraisers.
An appraiser often employs more than one approach to perform the valuation. In Eminent Domain or other litigation processes it is always recommended to use several approaches to establish convincing argument for the final property valuation.
Each appraisal approach, used in valuation, is influenced by a number of different factors. Some of the factors are used in several approaches and others are not shared by other approaches.
Typically, appraisers apply the sales comparison (Sales Comparison Approach), income capitalization (Income Approach) and cost (Cost Approach) individually. When more than one approach is applied, typically different values are obtained for each approach. After reviewing the reliability of data and analyzing the difference between valuation results, the appraiser determines the final value (reconciliation or correlation).
It should be noted that the reconciliation of all estimate values is typically required in Eminent Domain and other litigation cases, where the appraiser is required to substantiate the accuracy of his analysis.
Standards Rule 1-6 (USPAP 2003) states:
In developing a real property appraisal, an appraiser must:                (a) reconcile the quality of data available and analyzed within the approaches used; and        (b) reconcile the applicability or suitability of the approaches used to arrive at the value conclusion(s)        
In traditional appraisal practice, appraisers first determine various approaches that will best serve the valuation process for the subject property using specific data and factors pertaining to that approach. To facilitate the evaluation, each factor is then typically expressed as a single-point value. Obviously, any error in the assumed value for one or more selected factors will inevitably affect the final result. Generally, even Sensitivity Analysis check cannot fully eliminate these types of errors since this analysis only checks what happens if we adjust a factor value and cannot identify factors that might possibly be erroneous completely.
In order to arrive at a final conclusion of a value for the property, the appraiser must reconcile the different values obtained from different approaches. While some appraisers feel they should express the property value in a form of value ranges, very often they are required to provide a specific price figure, called point estimate. Clearly, by averaging the differing results from various estimates, another level of error is introduced into the final estimate already based on individually adjusted single values. Usually, appraisers are comparing valuation results from all different approaches and taking an average result as a final value. However, this would imply that each approach has equal strength and reliability which is rarely true.
Real estate appraisals are used in large variety of real estate transactions. They generally require considerable effort and time to prepare and are relatively expensive.
Little or no work deals directly with optimization programming in appraisal domain and especially in using all influence factors in all approaches together rather than in one approach. In appraisals and especially in litigation cases there is a strong need to prove the accuracy of valuation process and of the final result.